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Multiple SVM-RFE for multi-class gene selection on DNA Microarray data

机译:多个SVM-RFE用于DNA微阵列数据的多类基因选择

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This paper presents a new multi-class gene selection and classification method based on multiple support vector machine recursive feature elimination (SVM-RFE). For a multi-class DNA microarray problem, we solve it as multiple binary classification problems. First, the one-versus-all method is used to decompose the multi-class task into multiple binary problems. Second, an SVM-RFE is adopted to select genes for each binary problem. Then, an SVM classifier is used to train the selected gene data for a binary problem. Finally, we combine the outputs of multiple SVM classifiers. Experimental results on three DNA Microarray datasets show that the proposed method achieves higher classification accuracy.
机译:本文提出了一种基于多支持向量机递归特征消除(SVM-RFE)的多类别基因选择和分类的新方法。对于多类DNA微阵列问题,我们将其作为多个二元分类问题来解决。首先,使用“一对所有”方法将多类任务分解为多个二元问题。其次,采用SVM-RFE为每个二元问题选择基因。然后,使用SVM分类器来训练针对二元问题的选定基因数据。最后,我们结合了多个SVM分类器的输出。在三个DNA芯片数据集上的实验结果表明,该方法具有较高的分类精度。

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